How localized force spreads on elastic contour feathers

Birds can experience localized forces against their bodies due to impact against solid objects (like a branch or another bird) or water (during plunge-dives or landings). In this study, we hypothesize that densely packed contour feathers around the bird body would spread localized impact force while diving and maintaining plumage integrity. To test the hypothesis, we performed experiments with individual feathers and elastic beams, and developed a theoretical model to determine the response of feathers during the dive. First, we used a micro computed tomography scanner to characterize the internal structure of the contour feather from a northern gannet and calculate Young’s modulus of feathers sampled from different parts of the body. This value was found to be of the order of 10 9 Pa for feathers from chest and belly. Second, we model the feathers as elastic beams taking into account their pre-curvature and non-uniform cross-section. Results from our experiments with polycarbonate beams suggest that the interaction of feathers on the skin patch redistributes the force, thereby reducing the impact on any particular area of the skin. Finally, a theoretical model of multiple overlaying feathers is proposed to quantify the spreading of impact force on the skin of the bird body which shows that the pressure on the skin at the impact point can be reduced by as much as three times the pressure if feathers had been absent.

TRACKING MOVING CONTOURS USING ENERGY-MINIMIZING ELASTIC CONTOUR MODELS

This paper proposes a robust method for tracking an object contour in a sequence of images. In this method, both object extraction and tracking problems can be solved simultaneously. Furthermore, it is applicable to the tracking of arbitrary shapes since it does not need a priori knowledge about the object shapes. In the contour tracking, energy-minimizing elastic contour models are utilized, which is newly presented in this paper. The contour tracking is formulated as an optimization problem to find the position that minimizes both the elastic energy of its model and the potential energy derived from the edge potential image that includes a target object contour. We also present an algorithm which efficiently solves energy minimization problems within a dynamic programming framework. The algorithm enables us to obtain optimal solution even when the variables to be optimized are not ordered. We show the validity and usefulness of the proposed method with some experimental results.